Environments in which an autonomous vehicle may be tasked to navigate in may change over time due to changes in patterns of use (e.g., by pedestrians), road infrastructure (e.g., traffic signs, traffic lights, road markings, etc.) road conditions (e.g., road construction, a lane closure, potholes, an obstruction on a road surface, etc.). Changes in road conditions, such as lane closures, potholes and the like may require the autonomous vehicle to take appropriate actions to alter an initial guided path to a revised guided path. However, detecting events that may give rise to the need to implement a change may not be effective if the autonomous vehicle is not configured to predict a course of action to take based on a newly detected event. Moreover, information associated with an event and responses taken by the autonomous vehicle in response to the event may not benefit other autonomous vehicles that may also encounter a similar event unless the information and/or response is disseminated to the other autonomous vehicles.
Thus, what is needed is a solution to implement event detection that predicts optimal courses of action responsive to the event, without the limitations of conventional techniques.
Although the above-described drawings depict various examples of the invention, the invention is not limited by the depicted examples. It is to be understood that, in the drawings, like reference numerals designate like structural elements. Also, it is understood that the drawings are not necessarily to scale.